See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/225842575 Effects of spatial heterogeneity on butterfly species richness in Rocky Mountain National Park, CO, USA Article in Biodiversity and Conservation · March 2008 DOI: 10.1007/s10531-008-9536-8 CITATIONS READS 51 285 3 authors: Sunil Kumar Sara E. Simonson United States Department of Agriculture Colorado State University 107 PUBLICATIONS 2,969 CITATIONS 25 PUBLICATIONS 250 CITATIONS SEE PROFILE SEE PROFILE Thomas J. Stohlgren Colorado State University 243 PUBLICATIONS 13,198 CITATIONS SEE PROFILE Some of the authors of this publication are also working on these related projects: Semi-retirement! View project The Entomologist's Monthly Magazine Volume 154, pg: 65-78. Published January 26 2018 View project All content following this page was uploaded by Sunil Kumar on 02 June 2014. The user has requested enhancement of the downloaded file. Biodivers Conserv (2009) 18:739–763 DOI 10.1007/s10531-008-9536-8 ORIGINAL PAPER EVects of spatial heterogeneity on butterXy species richness in Rocky Mountain National Park, CO, USA Sunil Kumar · Sara E. Simonson · Thomas J. Stohlgren Received: 14 May 2008 / Accepted: 17 November 2008 / Published online: 11 December 2008 © Springer Science+Business Media B.V. 2008 Abstract We investigated butterXy responses to plot-level characteristics (plant species richness, vegetation height, and range in NDVI [normalized diVerence vegetation index]) and spatial heterogeneity in topography and landscape patterns (composition and conWgu- ration) at multiple spatial scales. StratiWed random sampling was used to collect data on butterXy species richness from seventy-six 20 £ 50 m plots. The plant species richness and average vegetation height data were collected from 76 modiWed-Whittaker plots overlaid on 76 butterXy plots. Spatial heterogeneity around sample plots was quantiWed by measur- ing topographic variables and landscape metrics at eight spatial extents (radii of 300, 600 to 2,400 m). The number of butterXy species recorded was strongly positively correlated with plant species richness, proportion of shrubland and mean patch size of shrubland. Patterns in butterXy species richness were negatively correlated with other variables including mean patch size, average vegetation height, elevation, and range in NDVI. The best predictive model selected using Akaike’s Information Criterion corrected for small sample size X (AICc), explained 62% of the variation in butter y species richness at the 2,100 m spatial extent. Average vegetation height and mean patch size were among the best predictors of butterXy species richness. The models that included plot-level information and topographic variables explained relatively less variation in butterXy species richness, and were improved signiWcantly after including landscape metrics. Our results suggest that spatial heterogeneity greatly inXuences patterns in butterXy species richness, and that it should be explicitly considered in conservation and management actions. Keywords Akaike’s information criterion · ButterXy species richness · FRAGSTATS · Landscape context · Landscape metrics · Model selection · Plant species richness · Spatial autocorrelation · Spatial heterogeneity · Spatial scale S. Kumar (&) · S. E. Simonson Natural Resource Ecology Laboratory, Colorado State University, 1499 Campus Delivery, A204 NESB Building, Fort Collins, CO 80523-1499, USA e-mail: [email protected]; [email protected] T. J. Stohlgren U.S. Geological Survey, Fort Collins Science Center, Fort Collins, CO 80526-8118, USA 1 C 740 Biodivers Conserv (2009) 18:739–763 Abbreviations AICc Akaike’s information criterion corrected for small sample size DEM Digital elevation model ESRI Environmental Systems Research Institute GIS Geographical information system GPS Global positioning system MODIS Moderate resolution imaging spectroradiometer NAD North American datum NASA National Aeronautics and Space Administration NDVI Normalized diVerence vegetation index NLCD National land cover dataset USGS United States Geological Survey Introduction Understanding how spatial heterogeneity aVects ecological patterns and processes is one of the major focuses of landscape ecology (Risser et al. 1984; Pickett and Cadenasso 1995; Turner et al. 2001; Fortin and Agrawal 2005; Turner 2005). Spatial heterogeneity can be deWned as the complexity and variability in ecological systems’ properties of interest in space (Li and Reynolds 1994). Quantifying spatial heterogeneity is needed to understand its eVects on the diversity and distributions of diVerent organisms and their species-speciWc responses (Gustafson 1998; Turner et al. 2001; Thies et al. 2003; Kumar et al. 2006). However, the decision at which scale to quantify spatial heterogeneity is one of the challenging questions that ecologists face because spatial heterogeneity is a complex phenomenon and is highly scale dependent (Kolasa and Rollo 1991; Gustafson 1998; Fortin and Agrawal 2005; Wagner and Fortin 2005). Spatial heterogeneity in ecological systems is caused by spatial interactions between many biotic and abiotic factors and the diVerential responses of organisms to these factors (Milne 1991) and the organisms themselves (Huston 1994). DiVerent organisms may have diVerential responses to spatial heterogeneity at multiple scales depending on their grain of perception (Levins 1968), the grain of the landscape (Forman and Godron 1986) and their natural history. Therefore, identiWcation of the factors that most inXuence species diversity, and the dominant scale (i.e., the scale that explains highest variation in the diversity and abundance of organisms) of response of species to these factors is important (Turner 2005) for maintaining and managing biodiversity. ButterXies and plants are generally predicted to show congruent patterns in species diversity due to ecological interactions involving herbivory and pollination (Opler and Krizek 1984; Scoble 1992), and their long history of mutual evolutionary inXuence (Ehrlich and Raven 1964). At local scales, many species of butterXies are restricted to one or a few closely related species of host plants that provide suitable food resources for the larvae (caterpillar; Opler 1999). Although butterXies require the suitable host plants as larval food resources, the geo- graphic distribution of a given butterXy is typically less extensive than the distribution of its potential host plants. A butterXy species may often be found near certain species of plants, but a butterXy will rarely be present in every area that the plant occurs. Across their ranges, butterXy species can show dramatic diVerences in breadth of host plant use and preferences for host plant species. The relative importance of individual plant species as butterXy host plants can vary in space, time, and even among individuals in the same population. 1 C Biodivers Conserv (2009) 18:739–763 741 The availability of Xoral nectar plant resources for adult butterXies can also be an impor- tant characteristic of the local vegetation. In a given area there is generally a greater variety of plant species that can potentially be used by butterXies as larval host plants than as nectar plants (Opler 1999). Nectar plants used by adult butterXies tend to be less speciWc than the host plants required by their larvae. A showy display of abundant nectar Xowers can be an attractive food resource for the adults of many diVerent butterXy species. However, there are examples of butterXy species that are linked closely with particular species of plants that they frequently visit for nectar resources. The diversity and distribution of plant species and characteristics of the vegetation may also inXuence patterns of butterXy species diversity by aVecting their movement and searching behavior (Kareiva 1983; Ricketts 2001). ButterXies can be sensitive to changes in environmental conditions such as vegetation structure, solar radiation, climate variabil- ity, weather events, and patterns in land-use (Wood and Samways 1991; Parmesan 1996; Fleishman et al. 2002; Luoto et al. 2006). Although it can be diYcult to determine the causal mechanisms underlying observed Xuctuations in butterXy populations, the rapid response of butterXies to changes in local vegetation and climate conditions suggests that they may be useful as indicators to monitor ecosystem properties and local habitats (Murphy and Weiss 1992; Kremen 1992; Pollard and Yates 1993; Parmesan 1996). For both practical and ecological reasons, butterXies have been suggested as potential indicator taxa to monitor ecosystems, habitat loss, non-native species invasion, fragmenta- tion, and climate change. Among insects, butterXies are well-studied, relatively easy to monitor, and have relatively short generation periods (Fleishman et al. 2002; Thomas 2005). For example, butterXies may exhibit rapid responses to disturbance events such as Wre and management activities such as logging because of their short generation time (Fleishman et al. 2002). ButterXy resources and their habitats often co-occur with other ecosystem properties of management interest, thus butterXies have also been proposed as indicator species for other taxa (Kremen 1992; Fleishman et al. 2002; Thomas 2005). Habitats used by butterXies may also support other lesser-known insect groups of conservation interest, including valuable plant pollinators such as moths, bees, ants, and Xies. ButterXies can also have important and diverse